{"author":[{"id":"582b06a9-1f1c-11ee-b076-82ffce00dde4","last_name":"Campbell","full_name":"Campbell, Andrew J","first_name":"Andrew J"},{"first_name":"Sean","full_name":"O’Rourke, Sean","last_name":"O’Rourke"}],"publication":"Journal of Theoretical Probability","department":[{"_id":"LaEr"}],"acknowledgement":"The first author thanks Yizhe Zhu for pointing out reference [30]. We thank David Renfrew for comments on an earlier draft. We thank the anonymous referee for a careful reading and helpful comments.\r\nOpen access funding provided by Institute of Science and Technology (IST Austria).","_id":"13975","status":"public","publication_status":"epub_ahead","month":"07","scopus_import":"1","oa_version":"Published Version","year":"2023","publication_identifier":{"issn":["0894-9840"],"eissn":["1572-9230"]},"language":[{"iso":"eng"}],"date_updated":"2023-12-13T12:00:50Z","date_created":"2023-08-06T22:01:13Z","publisher":"Springer Nature","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"26","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/s10959-023-01275-4"}],"has_accepted_license":"1","abstract":[{"lang":"eng","text":"We consider the spectrum of random Laplacian matrices of the form Ln=An−Dn where An\r\n is a real symmetric random matrix and Dn is a diagonal matrix whose entries are equal to the corresponding row sums of An. If An is a Wigner matrix with entries in the domain of attraction of a Gaussian distribution, the empirical spectral measure of Ln is known to converge to the free convolution of a semicircle distribution and a standard real Gaussian distribution. We consider real symmetric random matrices An with independent entries (up to symmetry) whose row sums converge to a purely non-Gaussian infinitely divisible distribution, which fall into the class of Lévy–Khintchine random matrices first introduced by Jung [Trans Am Math Soc, 370, (2018)]. Our main result shows that the empirical spectral measure of Ln  converges almost surely to a deterministic limit. A key step in the proof is to use the purely non-Gaussian nature of the row sums to build a random operator to which Ln converges in an appropriate sense. This operator leads to a recursive distributional equation uniquely describing the Stieltjes transform of the limiting empirical spectral measure."}],"isi":1,"external_id":{"isi":["001038341000001"],"arxiv":["2210.07927"]},"date_published":"2023-07-26T00:00:00Z","article_processing_charge":"Yes (via OA deal)","citation":{"apa":"Campbell, A. J., &#38; O’Rourke, S. (2023). Spectrum of Lévy–Khintchine random laplacian matrices. <i>Journal of Theoretical Probability</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s10959-023-01275-4\">https://doi.org/10.1007/s10959-023-01275-4</a>","mla":"Campbell, Andrew J., and Sean O’Rourke. “Spectrum of Lévy–Khintchine Random Laplacian Matrices.” <i>Journal of Theoretical Probability</i>, Springer Nature, 2023, doi:<a href=\"https://doi.org/10.1007/s10959-023-01275-4\">10.1007/s10959-023-01275-4</a>.","short":"A.J. Campbell, S. O’Rourke, Journal of Theoretical Probability (2023).","ista":"Campbell AJ, O’Rourke S. 2023. Spectrum of Lévy–Khintchine random laplacian matrices. Journal of Theoretical Probability.","ieee":"A. J. Campbell and S. O’Rourke, “Spectrum of Lévy–Khintchine random laplacian matrices,” <i>Journal of Theoretical Probability</i>. Springer Nature, 2023.","ama":"Campbell AJ, O’Rourke S. Spectrum of Lévy–Khintchine random laplacian matrices. <i>Journal of Theoretical Probability</i>. 2023. doi:<a href=\"https://doi.org/10.1007/s10959-023-01275-4\">10.1007/s10959-023-01275-4</a>","chicago":"Campbell, Andrew J, and Sean O’Rourke. “Spectrum of Lévy–Khintchine Random Laplacian Matrices.” <i>Journal of Theoretical Probability</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1007/s10959-023-01275-4\">https://doi.org/10.1007/s10959-023-01275-4</a>."},"doi":"10.1007/s10959-023-01275-4","article_type":"original","quality_controlled":"1","oa":1,"title":"Spectrum of Lévy–Khintchine random laplacian matrices","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"ddc":["510"]}